We introduce a time series model that captures both long memory and conditional heteroskedasticity and assess their ability to describe the US inflation data. Specifically, the model allows for long memory in the conditional mean formulation and uses a normal mixture GARCH process to...

We introduce a time series model that captures both long memory and conditional heteroskedasticity and assess their ability to describe the US inflation data. Specifically, the model allows for long memory in the conditional mean formulation and uses a normal mixture GARCH process to...

Estimates of the NAIRU are usually derived either from a Phillips curve or from a wage curve. This paper investigates the correspondence between the operational NAIRU-concepts and the steady state of a dynamic wage-price model. We derive the parameter restrictions that secure that...

Three classes of inflation models are discussed: Standard Phillips curves, New Keynesian Phillips curves and Incomplete Competition models. Their relative merits in explaining and forecasting inflation are investigated theoretically and empirically. We establish that Standard Phillips-curve...

The paper describes the influx of mathematical statistics in economics. It focuses on an approach to macroeconometric modelling which is based on fundamental statistical concepts like the joint distribution function of all observable variables for the whole sample period. The methodology relies...

This paper compares the performance of simple inflation targeting (IT) and price-level path targeting (PLPT) rules to stabilize the macroeconomy, in response to a series of shocks, similar to those seen in Canada and the United States over the 1983 to 2004 period. The analysis is conducted in a...

We introduce a time series model that captures both long memory and conditional heteroskedasticity and assess their ability to describe the US inflation data. Specifically, the model allows for long memory in the conditional mean formulation and uses a normal mixture GARCH process to...

We introduce a time series model that captures both long memory and conditional heteroskedasticity and assess their ability to describe the US inflation data. Specifically, the model allows for long memory in the conditional mean formulation and uses a normal mixture GARCH process to...

The estimation of inflation volatility is important to Central Banks as it guides their policy initiatives for achieving and maintaining price stability. This paper employs three models from the Generalized Autoregressive Conditional Heteroscedasticity (GARCH) family with a view to providing a...

This study analyses the performance of real estate mutual funds for 1993 through 2001 period. The results indicate that real estate mutual funds do not provide positive abnormal performance on average. Fund performance to a large extent is determined by the performance of the real estate sector...